
class 			A_  :




	'''simple docstring'''


	def __init__(			self						,       snake_case						,       snake_case			):
		lowercase	    =       name
		lowercase	    =       val





	def __str__(			self			):
		return F'''{self.__class__.__name__}({self.name}, {self.val})'''





	def __lt__(			self						,       snake_case			):
		return self.val < other.val







class 			A_  :




	'''simple docstring'''


	def __init__(			self						,       snake_case			):
		lowercase	    =       {}
		lowercase	    =       {}
		lowercase	    =       self.build_heap(snake_case			)





	def __getitem__(			self						,       snake_case			):
		return self.get_value(snake_case			)





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		return (idx - 1) // 2





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		return idx * 2 + 1





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		return idx * 2 + 2





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		return self.heap_dict[key]





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		lowercase	    =       len(snake_case			) - 1
		lowercase	    =       self.get_parent_idx(snake_case			)

		for idx, i in enumerate(snake_case			):
			lowercase	    =       idx
			lowercase	    =       i.val

		for i in range(snake_case						,       -1						,       -1			):
			self.sift_down(snake_case						,       snake_case			)
		return array





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case						,       snake_case			):
		while True:
			lowercase	    =       self.get_left_child_idx(snake_case			)  # noqa: E741
			lowercase	    =       self.get_right_child_idx(snake_case			)

			lowercase	    =       idx
			if l < len(snake_case			) and array[l] < array[idx]:
				lowercase	    =       l
			if r < len(snake_case			) and array[r] < array[smallest]:
				lowercase	    =       r

			if smallest != idx:
				lowercase    ,   lowercase	    =       array[smallest], array[idx]
				(
				    (
				    lowercase
				)    ,   (
				    lowercase
				)    ,   
				)	    =       (
				    self.idx_of_element[array[smallest]],
				    self.idx_of_element[array[idx]],
				)
				lowercase	    =       smallest
			else:
				break





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		lowercase	    =       self.get_parent_idx(snake_case			)
		while p >= 0 and self.heap[p] > self.heap[idx]:
			lowercase    ,   lowercase	    =       self.heap[idx], self.heap[p]
			lowercase    ,   lowercase	    =       (
			    self.idx_of_element[self.heap[idx]],
			    self.idx_of_element[self.heap[p]],
			)
			lowercase	    =       p
			lowercase	    =       self.get_parent_idx(snake_case			)





	def       SCREAMING_SNAKE_CASE__		(			self			):
		return self.heap[0]





	def       SCREAMING_SNAKE_CASE__		(			self			):
		lowercase    ,   lowercase	    =       self.heap[-1], self.heap[0]
		lowercase    ,   lowercase	    =       (
		    self.idx_of_element[self.heap[-1]],
		    self.idx_of_element[self.heap[0]],
		)

		lowercase	    =       self.heap.pop()
		del self.idx_of_element[x]
		self.sift_down(0						,       self.heap			)
		return x





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case			):
		self.heap.append(snake_case			)
		lowercase	    =       len(self.heap			) - 1
		lowercase	    =       node.val
		self.sift_up(len(self.heap			) - 1			)





	def       SCREAMING_SNAKE_CASE__		(			self			):
		return len(self.heap			) == 0





	def       SCREAMING_SNAKE_CASE__		(			self						,       snake_case						,       snake_case			):
		assert (
		    self.heap[self.idx_of_element[node]].val > new_value
		), "newValue must be less that current value"
		lowercase	    =       new_value
		lowercase	    =       new_value
		self.sift_up(self.idx_of_element[node]			)




UpperCAmelCase       =					Node('''R''', -1)
UpperCAmelCase       =					Node('''B''', 6)
UpperCAmelCase       =					Node('''A''', 3)
UpperCAmelCase       =					Node('''X''', 1)
UpperCAmelCase       =					Node('''E''', 4)

# Use one of these two ways to generate Min-Heap

# Generating Min-Heap from array
UpperCAmelCase       =					MinHeap([r, b, a, x, e])

# Generating Min-Heap by Insert method
# myMinHeap.insert(a)
# myMinHeap.insert(b)
# myMinHeap.insert(x)
# myMinHeap.insert(r)
# myMinHeap.insert(e)

# Before
print('''Min Heap - before decrease key''')
for i in my_min_heap.heap:
	print(i)

print('''Min Heap - After decrease key of node [B -> -17]''')
my_min_heap.decrease_key(b, -17)

# After
for i in my_min_heap.heap:
	print(i)

if __name__ == "__main__":
	import doctest

	doctest.testmod()







'''simple docstring'''


import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
UpperCAmelCase_					=   logging.getLogger()


def     SCREAMING_SNAKE_CASE							(   a_						:				Path					,       a_						:				list      ):
  __a								=       '\n'.join(a_      )
  Path(a_      ).open('w'      ).writelines(a_      )


UpperCAmelCase_					=   "patrickvonplaten/t5-tiny-random"
UpperCAmelCase_					=   "sshleifer/bart-tiny-random"
UpperCAmelCase_					=   "sshleifer/tiny-mbart"

UpperCAmelCase_					=   logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks





class  __lowercase    (	__magic_name__			):







   def 		UpperCamelCase__      (						self   ,				UpperCamelCase   )					->     Dict:
     __a								=       Path(self.get_auto_remove_tmp_dir()   ) / 'utest_input.source'
     __a								=       input_file_name.parent / 'utest_output.txt'
     assert not output_file_name.exists()
     __a								=       [' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.']
     _dump_articles(UpperCamelCase   ,				UpperCamelCase   )

     __a								=       str(Path(self.get_auto_remove_tmp_dir()   ) / 'scores.json'   )
     __a								=       'translation_en_to_de' if model == T5_TINY else 'summarization'
     __a								=       f"\n            run_eval_search.py\n            {model}\n            {input_file_name}\n            {output_file_name}\n            --score_path {score_path}\n            --task {task}\n            --num_beams 2\n            --length_penalty 2.0\n            ".split()

     with patch.object(UpperCamelCase   ,				'argv'   ,				UpperCamelCase   ):
       run_generate()
       assert Path(UpperCamelCase   ).exists()
       # os.remove(Path(output_file_name))







   def 		UpperCamelCase__      (						self   )					->     int:
     self.run_eval_tester(UpperCamelCase   )







   @parameterized.expand([BART_TINY, MBART_TINY]   )
   @slow
   def 		UpperCamelCase__      (						self   ,				UpperCamelCase   )					->     Union[str, Any]:
     self.run_eval_tester(UpperCamelCase   )







   @parameterized.expand([T5_TINY, MBART_TINY]   )
   @slow
   def 		UpperCamelCase__      (						self   ,				UpperCamelCase   )					->     Optional[Any]:
     __a								=       Path(self.get_auto_remove_tmp_dir()   ) / 'utest_input.source'
     __a								=       input_file_name.parent / 'utest_output.txt'
     assert not output_file_name.exists()

     __a								=       {
         'en': ['Machine learning is great, isn\'t it?', 'I like to eat bananas', 'Tomorrow is another great day!'],
         'de': [
             'Maschinelles Lernen ist großartig, oder?',
             'Ich esse gerne Bananen',
             'Morgen ist wieder ein toller Tag!',
         ],
     }

     __a								=       Path(self.get_auto_remove_tmp_dir()   )
     __a								=       str(tmp_dir / 'scores.json'   )
     __a								=       str(tmp_dir / 'val.target'   )
     _dump_articles(UpperCamelCase   ,				text['en']   )
     _dump_articles(UpperCamelCase   ,				text['de']   )
     __a								=       'translation_en_to_de' if model == T5_TINY else 'summarization'
     __a								=       f"\n            run_eval_search.py\n            {model}\n            {str(UpperCamelCase   )}\n            {str(UpperCamelCase   )}\n            --score_path {score_path}\n            --reference_path {reference_path}\n            --task {task}\n            ".split()
     testargs.extend(['--search', 'num_beams=1:2 length_penalty=0.9:1.0']   )

     with patch.object(UpperCamelCase   ,				'argv'   ,				UpperCamelCase   ):
       with CaptureStdout() as cs:
         run_search()
       __a								=       [' num_beams | length_penalty', model, 'Best score args']
       __a								=       ['Info']
       if "translation" in task:
         expected_strings.append('bleu'   )
       else:
         expected_strings.extend(UpperCamelCase   )
       for w in expected_strings:
         assert w in cs.out
       for w in un_expected_strings:
         assert w not in cs.out
       assert Path(UpperCamelCase   ).exists()
       os.remove(Path(UpperCamelCase   )   )



